Karthikeyan Shanmugam

Research Staff Member

I am currently a Research Staff Member at IBM Research AI, NY. Previously, I was a Herman Goldstine Postdoctoral Fellow in the Math Sciences Division at IBM Research, NY. I obtained my Ph.D. in Electrical and Computer Engineering from UT Austin in summer 2016. My advisor at UT was Alex Dimakis. I obtained my MS degree in Electrical Engineering (2010-2012) from the University of Southern California, B.Tech and M.Tech degrees in Electrical Engineering from IIT Madras in 2010.

My research interests broadly lie in Graph algorithms, Machine learning, Optimization, Coding Theory and Information Theory. In machine learning, my recent focus is on graphical model learning, causal inference interpretability in ML and large graph analytics. I also work on problems relating to information flow, storage and caching over networks.

Top Work

Reverse-engineering causal graphs with soft interventions

Reverse-engineering causal graphs with soft interventions

Causal Inference

Causal inference is expensive. Here’s an algorithm for fixing that.

Causal inference is expensive. Here’s an algorithm for fixing that.

Causal Inference

Publications with the MIT-IBM Watson AI Lab

Causal inference is expensive. Here’s an algorithm for fixing that.
Causal inference is expensive. Here’s an algorithm for fixing that.
 
Reverse-engineering causal graphs with soft interventions
Reverse-engineering causal graphs with soft interventions